On Thu, Jul 21, 2011 at 1:44 AM, Madana_Babu <madana_b...@infosys.com>wrote:
> Hi all, > > I have R installed on a box, which is running on a machine with 16 core and > Redhat - Linux. I am handling huge (size of dataset will be 5 GB) dataset. > Lets assume that my data is in the form of structured (multiple) logs. I > access the data by using all.files(). Since by default basic version of R > utilizes single core, the processing of my analysis code is taking too much > time. I got to know that mclapply() can be used to use all cores > (processors) to make R much faster when we have multicores. Can anyone help > me in understanding how to use mclapply() function in the above situation. > mclapply() works in the same way as lapply() - if you use lapply, simply replace it with mclapply, if you are using a loop, translate it into an lapply / mclapply structure. But be aware, that the bottleneck might be disk access!. So: rprof is your friend. Cheers, Rainer > Thanks in advance > > Regards, > Madana > > -- > View this message in context: > http://r.789695.n4.nabble.com/R-on-Multicore-for-Linux-tp3682318p3682318.html > Sent from the R help mailing list archive at Nabble.com. > > ______________________________________________ > R-help@r-project.org mailing list > https://stat.ethz.ch/mailman/listinfo/r-help > PLEASE do read the posting guide > http://www.R-project.org/posting-guide.html > and provide commented, minimal, self-contained, reproducible code. > -- Rainer M. Krug, PhD (Conservation Ecology, SUN), MSc (Conservation Biology, UCT), Dipl. Phys. (Germany) Centre of Excellence for Invasion Biology Stellenbosch University South Africa Tel : +33 - (0)9 53 10 27 44 Cell: +33 - (0)6 85 62 59 98 Fax (F): +33 - (0)9 58 10 27 44 Fax (D): +49 - (0)3 21 21 25 22 44 email: rai...@krugs.de Skype: RMkrug [[alternative HTML version deleted]] ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
